As the use of the Internet increases, there is a concomitant increase in the use of voice-over-IP (VoIP); i.e., the use of the Internet to transmit real-time voice conversations. This is attributed to the convergence of computing and telecommunications under a single umbrella. Given availability of the requisite bandwidth, advanced users opt for the immediacy of packet voice while engaged in an IP data application, as opposed to deriving voice associated with the application either from another medium, or at a later time.
The public Internet is a multi-node matrix of routers and switches joined by transport lines of differing capacities. As such, IP packets may experience processing delays at various nodes as they traverse the Internet matrix from one end-point to the next. Path differences can also lead to variations in arrival times of the IP voice packets, and this phenomenon, exaggerated by network congestion or other conditions, can have an adverse impact on the reconstruction of a voice conversation in real time. Link outages and traffic overload at specific nodes can also lead to packet losses, with a greater potential for negative impacts on the service. Anomalies in the behavior of the integrated network have therefore had limiting effects on the quality of IP voice applications.
To address those problems, standards bodies have improved protocol specifications, allowing greater predictability of the quality of service that a given application might support. However, beyond these protocol specifications, it is necessary to develop tools that are effective in defining and gauging service quality. For example, it would be desirable to provide a basis for raising customer acceptance levels, thus leading to the levels of confidence that are required for mass deployment
VoIP is a real-time conversational application, and in any one direction, the associated IP packet flow may be described as a real-time isochronous media stream. To maintain quality and media coherency in isochronous applications, strict time dependencies between the application bits must be observed within the destination end-system. The objective metrics that are generally used to describe the packet transport characteristics between two end-points within the Internet are delay, delay variation (also referred to as jitter), and packet loss. Delay refers to the time required to transmit an IP packet between two end-points within the Internet. Causes of delay include processing operations at routers within the network, increases in traffic load on the network side, and coding and packetization processing on the terminal side. Jitter refers to variations in the packet inter-arrival times from one end-system application to the next. Jitter is caused by fluctuations in network load, and differences in path routing of individual packets. Packet loss may refer either to arrivals that are so late as to render the packets unusable, or to the actual loss of packets. Packet loss is caused by network congestion, such as overloading at routers.
It is important to be able to control those end-to-end transport metrics to achieve quality VoIP. The capability to assess the state of those metrics also directly leads to the capability to set and predict the quality of service (QoS) that is supportable between two end-points within the Internet.
Much complexity is involved in quantifying the relationship between the raw end-to-end packet transport metrics and the perceived voice quality for a sample instantiation of IP voice. One viable approach to applying those transport metrics in determining VoIP QoS is a translation to Mean Opinion Scores (MOS) through the use of the E-Model. The E-Model is described in detail in ITU-T Recommendation G.107, “The E-Model, a Computational Model for Use in Transmission Planning” (December 1998), the contents of which is incorporated by reference herein in its entirety. MOS modeling has been in use for several years, and provides a psychological measure of voice quality. MOS scores are derived from the arithmetic average of a group of subjective responses. The technique is widely adopted for voice quality assessment. The E-Model is an analytic model of voice quality for use in network planning purposes. The E-Model provides a method for estimating the relative voice quality when comparing two reference connections. A highlight of the E-Model is the computation of the R-factor, which is used as a measure of voice quality. Once the R-factor is computed, the E-Model allows for straightforward mapping back to MOS scores. The R-factor itself is computed by methods using the network transport metrics as discussed in Cole, R. G. and Rosenbluth, J. H., “Voice over IP Performance Monitoring,” Computer Communication Review, V. 31, No. 2 at 9-14 (April 2001), the contents of which is incorporated by reference herein in its entirety.
The most common prior approach to prediction of QOS in the Internet involved the use of injecting echo probes into the network, and using the responses (or lack thereof) to those probes to measure the loss and round trip time (RTT). The RTT may then be used as a basis for estimating delay and jitter. The one-way delay is taken as one-half the measured RTT. That technique does not support in-service VoIP assessment and provisioning. Furthermore, the technique of injecting echo probes derives its metric information through the interface to routers in the network, and is therefore not amenable to implementation within the end-system or to integration with a VoIP application.
It is therefore desirable to provide a method and system for evaluating a quality of service (QoS) level for a communications service through measurement of the network transport metrics available at the end-system, and for modifying parameters to achieve a QoS level based on customer requirements.